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Paper Citation Record · LEDGER

Efficient Adversarial Training in LLMs with Continuous Attacks

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2405.15589.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2405.15589 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:49:08.845126Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

3
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 950b98c6-2587-4abd-96e1-16e11152d1d8 · inbound

Adversarial Reasoning at Jailbreaking Time cites this paper.

Adversarial Reasoning at Jailbreaking Time Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 48

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unresolved
no resolver link, observed 2026-08-09T14:49:08.845126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T14:49:08.845126Z digest=sha256:de659309dc5dbad1bae03f70b854e37ff51bb0a8249c3de931d91e0bd60f209a

Observation 6ebfcde3-9af6-40d6-8439-04f0f2a2fb40 · inbound

Confidence Elicitation: A New Attack Vector for Large Language Models cites this paper.

Confidence Elicitation: A New Attack Vector for Large Language Models Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 60

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no resolver link, observed 2026-08-08T22:06:39.000036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:39.000036Z digest=sha256:28bd4ad261f556acff0c78641e472e932aeb3bfc90856b8f17a071a62af1e4ee

Observation 0bf8c76c-ecb1-4d01-a8c8-a7a07a00873c · inbound

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities cites this paper.

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 78

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no resolver link, observed 2026-08-09T14:47:15.372451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:47:15.372451Z digest=sha256:86d372f1c5872948a31c74e9ea653ea33a009ad167d684c6828ba2f9c1526201

Observation 59c4f802-0764-4ad6-a548-bd128267c459 · inbound

Jailbreaking to Jailbreak cites this paper.

Jailbreaking to Jailbreak Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 46

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unresolved
no resolver link, observed 2026-08-08T17:02:47.456935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:02:47.456935Z digest=sha256:6a8dd0881dacd142c204ecdb0bcebd4d9c00088a469b4972aecaf2631137c490

Observation 2f10703b-0917-4198-963a-5a4b71051455 · inbound

Fast Proxies for LLM Robustness Evaluation cites this paper.

Fast Proxies for LLM Robustness Evaluation Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 21

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unresolved
no resolver link, observed 2026-08-07T19:32:24.135448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:32:24.135448Z digest=sha256:034095c2cd4c5067d61ff80aad1fdd12a4fdbd1c842c83b14377944b31c9bcd6

Observation 8888102b-66c1-414a-829f-d0d6ff0649db · inbound

LLM-Safety Evaluations Lack Robustness cites this paper.

LLM-Safety Evaluations Lack Robustness Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 56

Resolution
verified exact
arxiv_id, observed 2026-05-23T01:27:21.197788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-23T01:26:45.402983Z digest=sha256:8c5780615dbd3b218a2e376df538ebb8a05aa97c6e54b194c7897a7a92ab4426

Observation bbcee3d7-8de2-4d4f-a310-df21ca0b17e2 · inbound

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning cites this paper.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 56

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unresolved
no resolver link, observed 2026-08-07T15:37:30.568678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:37:30.568678Z digest=sha256:6e669e625c1f8970e74c7da3c3325f8668bb85ad5ed81110c0d0990d2d94eb7e

Observation 1a00d13a-b17d-4e84-b097-9e4b0406ccff · inbound

LLM-Powered AI Agent Systems and Their Applications in Industry cites this paper.

LLM-Powered AI Agent Systems and Their Applications in Industry Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 118

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verified exact
arxiv_id, observed 2026-05-22T14:06:38.048108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-22T14:05:54.535411Z digest=sha256:ebdf43a845e76fd8514791918877740232899faccc894b8310fa860ea94bfabd

Observation f6189f84-052e-4cbb-beb9-8ffa98a70cb5 · inbound

Adversarial Preference Learning for Robust LLM Alignment cites this paper.

Adversarial Preference Learning for Robust LLM Alignment Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 40

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unresolved
no resolver link, observed 2026-08-07T12:35:22.946436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:22.946436Z digest=sha256:9402530cae932c0e29e193292f2a64ce262f6bcf1f2af06d3dad2982d9a840cc

Observation 2033bf75-41f1-4ab5-8e01-a3f3876b678b · inbound

Align is not Enough: Multimodal Universal Jailbreak Attack against Multimodal Large Language Models cites this paper.

Align is not Enough: Multimodal Universal Jailbreak Attack against Multimodal Large Language Models Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T11:51:33.211141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:51:33.211141Z digest=sha256:8e9f98e41e6b79dd4f121c60b3c402fcb4e17993dcebaf9ad43cb06548de40f4

Observation d2467726-156b-4060-ab54-637a8a6d5571 · inbound

FORTRESS: Frontier Risk Evaluation for National Security and Public Safety cites this paper.

FORTRESS: Frontier Risk Evaluation for National Security and Public Safety Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 67

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unresolved
no resolver link, observed 2026-08-07T00:15:04.775172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:15:04.775172Z digest=sha256:d3bd9e034a5bff4aa09e659ea8281ce7bf348263619bd0ed555836f5adc68b39

Observation 96e2bd2b-d6c5-46b9-9f9d-6af4b1dbf148 · inbound

Report on NSF Workshop on Science of Safe AI cites this paper.

Report on NSF Workshop on Science of Safe AI Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T23:01:43.193726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:01:43.193726Z digest=sha256:53cc4a6a84724e134c802e00d343c841360a8c002266c6c66a3b93495df877a0

Observation e06d62fa-6e15-40be-b095-bc0bb8cb5e63 · inbound

Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol cites this paper.

Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-05T14:55:57.009096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:55:57.009096Z digest=sha256:22319456db61b75e0e25718d2506af1924aaf78eaddc341b28116c45a221c029

Observation 10907d11-eb26-4624-8e5a-ca60906594c0 · inbound

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data cites this paper.

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 130

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verified exact
arxiv_id, observed 2026-05-13T05:57:21.491083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-13T05:56:38.042978Z digest=sha256:a4a8829c0745e9d3fc654a0fd6c02afe3e199d58c2491f8762ed90232cb6e89c

Observation 6f06e21d-8ac0-4d06-991e-7165bdc47a8c · inbound

REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations cites this paper.

REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 39

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verified exact
arxiv_id, observed 2026-05-14T20:17:56.687435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-14T20:13:10.814899Z digest=sha256:24ee1cb293366087a769e5c4520828e523df3127ba03805b4ced3e0a9c039797

Observation 83cd2f77-216e-4bce-987c-b1f45eafbf14 · inbound

Codec-Robust Attacks on Audio LLMs cites this paper.

Codec-Robust Attacks on Audio LLMs Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-21T06:44:00.733588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T06:43:52.735211Z digest=sha256:0d240650626a5d163778c03b9727c0290ab54f65bca8cbe49a9e94262a924b58

Observation 0137dc81-b90f-4960-8bcc-fe290b33cb97 · inbound

Codec-Robust Attacks on Audio LLMs cites this paper.

Codec-Robust Attacks on Audio LLMs Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:45:23.661871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-25T05:44:46.831360Z digest=sha256:1bb904d59a8fab7bd80e6283dc4e848ab21d636d7462b4c6e86c4d37c824932e

Observation 00bd6111-073e-4961-8bad-b910a3b996a0 · inbound

Harnessing non-adversarial robustness in large language models cites this paper.

Harnessing non-adversarial robustness in large language models Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 20

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verified exact
arxiv_id, observed 2026-06-29T07:23:13.339293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-29T07:13:15.149708Z digest=sha256:eaadd0789fa80dc80eb4cae3035b1d83fad0119a140e50cefa81478f30d2013e

Observation e87352ac-2433-4c41-a1b2-338861814247 · inbound

CHASE: Adversarial Red-Blue Teaming for Improving LLM Safety using Reinforcement Learning cites this paper.

CHASE: Adversarial Red-Blue Teaming for Improving LLM Safety using Reinforcement Learning Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 36

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verified exact
arxiv_id, observed 2026-07-02T12:06:55.631034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T02:34:26.334078Z digest=sha256:234e190dda1d067b719f20576a3827d5b6d4085f4406bb43c95fbdb2fd6c3cd3

Observation 6cb77377-5147-4dc2-8859-5a74d98068fb · inbound

Efficient Safety Alignment of Language Models via Latent Personality Traits cites this paper.

Efficient Safety Alignment of Language Models via Latent Personality Traits Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 49

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verified exact
local_arxiv, observed 2026-07-10T15:27:20.099694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T15:26:23.290009Z digest=sha256:f71ef33faafe662165469c1c289afef89de7a6788382cd8ec9089244d0f83ffe